sustainability

Article

Evaluation of the Life Cycle Greenhouse GasEmissions from Hydroelectricity Generation Systems

Akhil Kadiyala 1, Raghava Kommalapati 1,2,* and Ziaul Huque 1,3

1 Center for Energy & Environmental Sustainability, Prairie View A&M University, Prairie View, TX 77446,USA; akkadiyala@pvamu.edu (A.K.); zihuque@pvamu.edu (Z.H.)

2 Department of Civil & Environmental Engineering, Prairie View A&M University, Prairie View,TX 77446, USA

3 Department of Mechanical Engineering, Prairie View A&M University, Prairie View, TX 77446, USA* Correspondence: rrkommalapati@pvamu.edu; Tel.: +1-936-261-1660

Academic Editor: Francesco AsdrubaliReceived: 28 March 2016; Accepted: 1 June 2016; Published: 8 June 2016

Abstract: This study evaluated the life cycle greenhouse gas (GHG) emissions from differenthydroelectricity generation systems by first performing a comprehensive review of thehydroelectricity generation system life cycle assessment (LCA) studies and then subsequentcomputation of statistical metrics to quantify the life cycle GHG emissions (expressed in gramsof carbon dioxide equivalent per kilowatt hour, gCO2e/kWh). A categorization index (with uniquecategory codes, formatted as “facility type-electric power generation capacity”) was developed andused in this study to evaluate the life cycle GHG emissions from the reviewed hydroelectricitygeneration systems. The unique category codes were labeled by integrating the names of the twohydro power sub-classifications, i.e., the facility type (impoundment (I), diversion (D), pumpedstorage (PS), miscellaneous hydropower works (MHPW)) and the electric power generation capacity(micro (µ), small (S), large (L)). The characterized hydroelectricity generation systems were statisticallyevaluated to determine the reduction in corresponding life cycle GHG emissions. A total of eightunique categorization codes (I-S, I-L, D-µ, D-S, D-L, PS-L, MHPW-µ, MHPW-S) were designatedto the 19 hydroelectricity generation LCA studies (representing 178 hydropower cases) using theproposed categorization index. The mean life cycle GHG emissions resulting from the use of I-S(N = 24), I-L (N = 8), D-µ (N = 3), D-S (N = 133), D-L (N = 3), PS-L (N = 3), MHPW-µ (N = 3), andMHPW-S (N = 1) hydroelectricity generation systems are 21.05 gCO2e/kWh, 40.63 gCO2e/kWh,47.82 gCO2e/kWh, 27.18 gCO2e/kWh, 3.45 gCO2e/kWh, 256.63 gCO2e/kWh, 19.73 gCO2e/kWh,and 2.78 gCO2e/kWh, respectively. D-L hydroelectricity generation systems produced the minimumlife cycle GHGs (considering the hydroelectricity generation system categories with a representationof at least two cases).

Keywords: life cycle assessment; greenhouse gas emissions; hydro energy; impoundment; diversion;pumped storage; miscellaneous hydropower works; electricity generation

1. Introduction

Hydro energy may be defined as the energy harnessed from flowing water through a turbineto generate electricity. The principal components that help generate electricity from hydroelectricplants are the hydraulic turbine, the electric generator, the transformers and power house, and thereservoir [1]. A hydraulic turbine comprises of a row of blades connected to a rotating shaft. Whenthe flowing water comes in contact with the blades of the turbine, the shaft of the hydraulic turbineis rotated due to its impact (change of velocity and pressure). The electric generator converts themechanical energy from the rotation of the shaft into electric power by rotating a series of coils inside

Sustainability 2016, 8, 539; doi:10.3390/su8060539 www.mdpi.com/journal/sustainability

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a magnetic field or vice versa, which results in the movement of electrons inside conductors thatproduces electric current. The transformers and power house of a hydropower plant act as an interfacebetween the electric generator and the power transmission lines. The reservoirs store water before themovement through hydraulic turbines. The reservoir may be located either upstream (water flowsunder gravity) or downstream of the discharge end of the water turbine (water is pumped back).

The total electricity generation in 2012 across the world was reported to be 21.53 trillion kilowatthours (kWh) [2]. The projected increase in world electricity generation for 2040 is 39 trillion kWh(81%) [3]. The renewable energy sources have been projected to account for 9.6 trillion kWh (25%) of theworld’s total electricity generation in 2040. With the continuing depletion of traditional non-renewableenergy sources, the necessity for generating electricity through the use of renewable energy sources(hydro, wind, biomass, solar, geothermal) increased significantly. Based on the 2012 statistics, hydroenergy was identified to be the largest renewable energy source for electricity generation with acontribution of 3.646 trillion kWh that accounted for 16.94% of the world’s total electricity generatedin 2012 [2].

Considering the significant role that hydroelectricity generation systems have to play in meetingthe world’s electrical energy demand, one needs to evaluate the life cycle greenhouse gas (GHG)emissions resulting from the adoption of different categories of hydroelectricity generation systems.The life cycle assessment (LCA) approach helps evaluate the net carbon dioxide (CO2) emissionsresulting from the use of hydro energy as a fuel. LCA is an analytical method that provides anassessment of the environmental impacts of the considered products and technologies from a “cradleto grave” systems perspective utilizing the detailed input and output parameters that operate withinthe designated system boundaries.

Many studies [4–22] analyzed the LCA of hydroelectricity generation systems. The use ofhydroelectricity generation systems across the world is being encouraged considering that wateris a free and an abundant renewable energy resource. The development of hydroelectricity generationsystems provides additional benefits such as the development of recreational opportunities (fishing,swimming, boating), flood control, irrigation, water supply, and back-up power during major electricityoutages or disruptions. The use of hydroelectricity generation systems has the disadvantages ofimpacting the fish population (with restrictions on the movement of fish between upstream anddownstream water bodies), low dissolved oxygen levels in the water that impacts the riverbankhabitats, drought conditions limiting the water supply, and high construction costs leading tohigher payback time for economical returns. A more detailed description of the LCA boundaryconditions, GHG emissions, and site-specific characteristics associated with each of the aforementionedhydroelectricity generation system studies are provided in the section titled “Review of HydroLCA Studies”.

All the hydro LCA publications to date have emphasized on the determination of the life cycleGHG emissions for site-specific hydroelectricity generation system installations. There are limitedstudies [23–26] that summarized the life cycle GHG emissions from hydroelectricity generation systems.None of the earlier LCA review studies evaluated and compared the life cycle GHG emissions across adistinct set of hydroelectricity generation system categories. This study aims to fill this knowledge gapby performing a comprehensive review of the literature on all the currently available hydroelectricitygeneration LCA studies, followed by a statistical evaluation of the life cycle GHG emissions fromthe reviewed hydroelectricity generation system categories distinctly. The results from the statisticalevaluation of the life cycle GHG emissions will assist energy policy makers and environmentalprofessionals in identifying and encouraging the use of environmental-friendly hydroelectricitygeneration system category options to generate electricity with minimal GHG emissions.

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2. Methodology

A review of the literature showed that the hydroelectricity generation systems may be categorizedon the basis of the type of facility and the electric power generation capacity. The classification ofhydroelectricity generation systems on the basis of facility type [27] is as follows:

‚ impoundment (I)—The impoundment is the most common type of facility. The facility has a damthat stores water in the reservoir and generates electricity when moving water rotates the turbines.

‚ diversion (D)—The diversion facility, also referred to as the run-of-river facility, diverts a section ofriver water through a canal or penstock to generate electricity. The use of a dam is not mandatoryin the diversion facility.

‚ pumped storage (PS)—The pumped storage facility uses energy from other sources (e.g., solar,wind, etc.) to pump water uphill from a lower reservoir to an upper reservoir during periods oflow energy demand. Water from the upper reservoir flows back into the lower reservoir duringperiods of high energy demand and generates electricity.

In addition to the aforementioned facility-based classification systems, this study considered thecategory of miscellaneous hydropower works (MHPW), which utilizes existing water infrastructuressuch as the water distribution networks, canal locks, compensation flows, water treatment works, etc.,to generate electricity in small quantities that can either be used on-site or transmitted for consumptionby a small community locally.

Depending on the electric power generation capacity, hydroelectricity generation systems may becategorized [27] as follows:

‚ micro (µ)—electricity generation capacity is less than 0.1 megawatt (MW).‚ small (S)—electricity generation capacity is between than 0.1 and 30 MW.‚ large (L)—electricity generation capacity is greater than 30 MW.

This study proposed and adopted the use of a new categorization index that integrated the namesof both the classification systems mentioned above to generate unique category codes, represented by“facility type-electric power generation capacity” labels to categorize the hydroelectricity generationsystems. A total of 12 unique category codes (I-µ, I-S, I-L, D-µ, D-S, D-L, PS-µ, PS-S, PS-L, MHPW-µ,MHPW-S, MHPW-L) may be generated using different combinations of the two classification systems.Each of the reviewed hydro LCA studies was first assigned one of the unique category codes proposedin this study. Next, the life cycle GHG emissions from the individual category coded hydroelectricitygeneration systems were evaluated using statistical metrics (sample size, mean, standard deviation,minimum, maximum, standard error of the mean, quartile 1, quartile 2 or median, quartile 3) andgraphical representations (error bars representing the mean with 95% confidence intervals, box plotsrepresenting the quartiles with outliers). While the error bars demonstrate the degree of confidence inthe mean GHG emissions, the box plots provide information on the degree of variation among theLCA studies characterized by different categories of hydroelectricity generation systems.

3. Results and Discussion

3.1. Review of Hydro LCA Studies

There are several studies [4–22] that evaluated the life cycle environmental impacts of using hydroenergy for electricity generation. One has to define the system boundary conditions (that includesdetails on the activities or processes to be considered in the analysis) and a functional unit of measure(that enables quantification of the net environmental impacts from carrying out an activity or a processas defined within the LCA system boundary conditions) when performing a LCA.

The majority of the reviewed LCA studies [9,14,15,18–20,22] considered the system boundariesthat included activities related to the construction, operation, and maintenance of the hydroelectricity

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generation systems. Other studies [7,11,13,16,17] adopted the system boundaries to include theraw material extraction, material processing, component manufacturing process, transportation,assembly and installation, operation and maintenance, and end-of-life process (decommissioning,recycling/reuse, and final disposal) activities. Gallagher et al. [21] excluded the end-of-life processactivity and considered the remaining activities listed within the system boundaries defined by otherstudies [7,11,13,16,17]. Ribeiro and Silva [10] considered the construction site operations, emissionsfrom reservoir flooding, and worker transportation activities within their system boundaries in additionto those associated with other studies [7,11,13,16,17]. Gagnon and van de Vate [4] performed the LCAof hydroelectricity generation systems with system boundaries that considered all the activities relatedto construction, the preparation of flooded land (biomass decay in the flooded lands), and the useof thermal backup power. Denholm and Kulcinski [5], and Suwanit and Gheewala [12] had systemboundary conditions that included the activities of land preparation before construction, construction,operation and maintenance, and decommissioning. Hondo [6] considered only electric generationactivity as the system boundary when performing the LCA of a hydroelectricity generation system.Rule et al. [8] considered the activities of construction, transportation, and decommissioning (50%recycling + 50% landfill for materials that are recyclable; 100% landfill for all other materials) as thesystem boundaries in their LCA.

The common functional unit of measure adopted by the majority of the hydro LCA studiesis grams of CO2 equivalent per kilowatt hour (gCO2e/kWh) of electricity produced. Accordingly,this study also adopts the functional unit of measure for GHG emissions to be gCO2e/kWh ofelectricity produced.

Table 1 provides a summary of the hydroelectricity generation system categorization (uniquecategory codes generated from the combination of the two classification systems—facility type (I, D,PS, MHPW), electric power generation capacity (µ, S, L) along with the corresponding GHG emissions(in gCO2e/kWh) for the reviewed hydro studies. Table 1 also provides additional site-specific detailsthat included the electricity generation capacity (EGC, expressed in MW), the capacity factor (CF,expressed in %), the hydropower plant life (PL, in years), and the geographical location (GL) for theinstalled hydroelectricity generation systems. EGC is the amount of electrical power that is producedunder standard operating conditions. CF is the ratio of the average power generated to the ratedpeak power.

Based on the review of 19 hydroelectricity generation LCA studies (refer to Table 1), one maynote that the D-S (N = 133) hydroelectricity generation systems were more in number compared toI-S (N = 24), I-L (N = 8), D-µ (N = 3), D-L (N = 3), PS-L (N = 3), MHPW-µ (N = 3), and MHPW-S(N = 1) hydroelectricity generation systems. There were no LCA studies on the use of I-µ, PS-µ, PS-S,and MHPW-L hydroelectricity generation systems. This is because the capital investments associatedwith the construction and maintenance of the impoundment and pumped storage hydroelectricitygeneration systems are considerably higher, which makes the generation of electricity at micro andsmall scale levels to not be feasible. The miscellaneous hydropower works are not feasible forlarge-scale electricity generation as they are designed for optimization and generation of electricityutilizing existing waterworks in small quantities for localized consumption. From Table 1, one may alsonote that the diversion hydroelectricity generation systems (N = 139) were more in number comparedto the impoundment (N = 32), the miscellaneous hydropower works (N = 4), and the pumped storage(N = 3) systems, and small hydroelectricity generation systems (N = 158) were more in numbercompared to the large hydroelectricity generation systems (N = 14) and the micro hydroelectricitygeneration systems (N = 6).

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Table 1. GHG emissions from hydroelectricity generation systems.

Source

CategorizationGHG Emissions

(gCO2e/kWh)

Additional Features

FacilityType

Electric PowerGeneration Capacity

UniqueCategory Code EGC (MW); CF (%); PL (years); GL

Gagnon and van de Vate [4] I L I-L 237 EGC = 4000; PL = 100; GL = Japan

Denholm and Kulcinski [5] PS L PS-L 5.6 EGC = 31-2100; CF = 20; PL = 60; GL = USA

Hondo [6] D S D-S 11.3 EGC = 10; CF = 45; PL = 30; GL = Japan

Pehnt [7]D S D-S 10 EGC = 3.1; GL = GermanyD S D-S 13 EGC = 0.3; GL = Germany

Rule et al. [8] I L I-L 4.6 EGC = 432 (4 ˆ 108); PL = 100; GL = New Zealand

Environmental Product Declaration Report [9] D L D-L 3.16 EGC = 50; PL = 100; GL = Aargau, Switzerland

Ribeiro and Silva [10] I L I-L 1.56 EGC = 14000; PL =100; GL = Brazil-Paraguay

Pascale et al. [11] MHPW µ MHPW-µ 52.7 EGC = 0.003; CF = 53; PL = 20; GL = Thailand

Suwanit and Gheewala [12]

D S D-S 11.01 EGC = 5.1; PL = 100; GL = ThailandD S D-S 23.01 EGC = 6 (2 ˆ 3); PL = 100; GL = ThailandD S D-S 16.28 EGC = 2.5 (2 ˆ 1.25); PL = 100; GL = ThailandD S D-S 22.71 EGC = 2.25; PL = 100; GL = ThailandD S D-S 16.49 EGC = 1.15; PL = 100; GL = Thailand

Flury and Frischknecht [13]

I L I-L 5.86 EGC = 95; PL = 150; GL = alpine, EuropeI L I-L 16.64 EGC = 95; PL = 150; GL = non-alpine, Europe

PS L PS-L 155.1 EGC = 95; PL = 150; GL = SwitzerlandPS L PS-L 609.2 EGC = 95; PL = 150; GL = EuropeD S D-S 3.62 EGC = 8.6; PL = 80; GL = SwitzerlandD S D-S 3.79 EGC = 8.6; PL = 80; GL = Europe

National Energy Technology Laboratory Report [14] I L I-L 43.8 EGC = 2080; PL = 80; GL = USA

Varun et al. [15]

D S D-S 26.41 EGC = 1; PL = 30; GL = Karnataka, IndiaD S D-S 25.52 EGC = 1.5; PL = 30; GL = Karnataka, IndiaD S D-S 28.14 EGC = 1; PL = 30; GL = Karnataka, IndiaD S D-S 30.33 EGC = 0.25; PL = 30; GL = Karnataka, IndiaD S D-S 16.44 EGC = 4.5; PL = 30; GL = Rajasthan, IndiaD S D-S 15.44 EGC = 4.5; PL = 30; GL = Rajasthan, IndiaD S D-S 15.85 EGC = 4 (2 ˆ 2); PL = 30; GL = Rajasthan, IndiaD S D-S 31.19 EGC = 0.85; PL = 30; GL = Karnataka, IndiaD S D-S 24.19 EGC = 1.5; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 19.99 EGC = 3; PL = 30; GL = Karnataka, IndiaD S D-S 31.11 EGC = 0.8 (2 ˆ 0.4); PL = 30; GL = Andhra Pradesh, IndiaD S D-S 29.97 EGC = 0.8; PL = 30; GL = Andhra Pradesh, India

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Table 1. Cont.

Source

CategorizationGHG Emissions

(gCO2e/kWh)

Additional Features

FacilityType

Electric PowerGeneration Capacity

UniqueCategory Code EGC (MW); CF (%); PL (years); GL

Varun et al. [15]

D S D-S 27.96 EGC = 2 (2 ˆ 1); PL = 30; GL = Andhra Pradesh, IndiaD S D-S 25.27 EGC = 2 (2 ˆ 1); PL = 30; GL = Andhra Pradesh, IndiaD S D-S 33.12 EGC = 0.65; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 28.75 EGC = 0.8; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 23.8 EGC = 2 (2 ˆ 1); PL = 30; GL = Andhra Pradesh, IndiaD S D-S 26.33 EGC = 2.14 (2 ˆ 1.07); PL = 30; GL = Andhra Pradesh, IndiaD S D-S 28.67 EGC = 1.588 (2 ˆ 0.794); PL = 30; GL = Andhra Pradesh, IndiaD S D-S 26.16 EGC = 2.47 (2 ˆ 1.235); PL = 30; GL = Andhra Pradesh, IndiaD S D-S 35.97 EGC = 0.5; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 37.56 EGC = 0.5; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 38.25 EGC = 0.55; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 35.64 EGC = 0.55; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 33.44 EGC = 0.5; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 27.1 EGC = 3.3 (2 ˆ 1.65); PL = 30; GL = Andhra Pradesh, IndiaD S D-S 32.71 EGC = 0.5; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 30.43 EGC = 0.8 (2 ˆ 0.4); PL = 30; GL = Andhra Pradesh, IndiaD S D-S 23.34 EGC = 2 (2 ˆ 1); PL = 30; GL = Andhra Pradesh, IndiaD S D-S 32.37 EGC = 0.55; PL = 30; GL = Tamilnadu, IndiaD S D-S 29.56 EGC = 0.8; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 26.51 EGC = 3.3 (2 ˆ 1.65); PL = 30; GL = Andhra Pradesh, IndiaD S D-S 20.56 EGC = 7.5 (3 ˆ 2.5); PL = 30; GL = Andhra Pradesh, IndiaD S D-S 28.92 EGC = 1; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 32.71 EGC = 0.65; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 23.74 EGC = 1.85; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 24.89 EGC = 1.7; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 25.42 EGC = 1.7; PL = 30; GL = Andhra Pradesh, IndiaD S D-S 20.39 EGC = 3.75 (3 ˆ 1.25); PL = 30; GL = Andhra Pradesh, IndiaD S D-S 28.17 EGC = 1 (2 ˆ 0.5); PL = 30; GL = Bihar, IndiaD S D-S 33.31 EGC = 0.7 (2 ˆ 0.35); PL = 30; GL = Bihar, IndiaD S D-S 28.18 EGC = 1 (2 ˆ 0.5); PL = 30; GL = Bihar, IndiaD S D-S 31.56 EGC = 0.5; PL = 30; GL = Bihar, IndiaD S D-S 41.75 EGC = 0.25; PL = 30; GL = Bihar, IndiaD S D-S 28.19 EGC = 1 (2 ˆ 0.5); PL = 30; GL = Bihar, IndiaD S D-S 39.77 EGC = 0.5 (2 ˆ 0.25); PL = 30; GL = Bihar, IndiaD S D-S 23.38 EGC = 1.5 (2 ˆ 0.75); PL = 30; GL = Bihar, IndiaD S D-S 26.12 EGC = 1 (2 ˆ 0.5); PL = 30; GL = Bihar, IndiaD S D-S 21.2 EGC = 3 (2 ˆ 1.5); PL = 30; GL = Karnataka, India

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Table 1. Cont.

Source

CategorizationGHG Emissions

(gCO2e/kWh)

Additional Features

FacilityType

Electric PowerGeneration Capacity

UniqueCategory Code EGC (MW); CF (%); PL (years); GL

Varun et al. [15]

D S D-S 22.15 EGC = 2.8; PL = 30; GL = Karnataka, IndiaD S D-S 24.29 EGC = 1.3; PL = 30; GL = Karnataka, IndiaD S D-S 36.4 EGC = 0.25; PL = 30; GL = Madhya Pradesh, IndiaD S D-S 28.07 EGC = 1 (2 ˆ 0.5); PL = 30; GL = Madhya Pradesh, IndiaD S D-S 32.02 EGC = 1.4 (2 ˆ 0.7); PL = 30; GL = Punjab, IndiaD S D-S 32.05 EGC = 1.5 (2 ˆ 0.75); PL = 30; GL = Punjab, IndiaD S D-S 32.05 EGC = 1.5 (2 ˆ 0.75); PL = 30; GL = Punjab, IndiaD S D-S 31.04 EGC = 1.5 (2 ˆ 0.75); PL = 30; GL = Punjab, IndiaD S D-S 35.12 EGC = 0.535; PL = 30; GL = Rajasthan, IndiaD S D-S 27.55 EGC = 1.2; PL = 30; GL = Rajasthan, IndiaD S D-S 22.85 EGC = 2.25 (3 ˆ 0.75); PL = 30; GL = Tamilnadu, IndiaD S D-S 31.29 EGC = 0.75; PL = 30; GL = West Bengal, IndiaI S I-S 31.2 EGC = 1 (2 ˆ 0.5); PL = 30; GL = Bihar, IndiaI S I-S 33.86 EGC = 0.4 (2 ˆ 0.2); PL = 30; GL = Bihar, IndiaI S I-S 23.9 EGC = 15; PL = 30; GL = Maharashtra, IndiaI S I-S 25.6 EGC = 1.5 (2 ˆ 0.75); PL = 30; GL = Karnataka, IndiaI S I-S 16.63 EGC = 10; PL = 30; GL = Andhra Pradesh, IndiaI S I-S 26.6 EGC = 1.5; PL = 30; GL = Karnataka, IndiaI S I-S 21.46 EGC = 2; PL = 30; GL = Andhra Pradesh, IndiaI S I-S 15.1 EGC = 15 (2 ˆ 7.5); PL = 30; GL = Andhra Pradesh, IndiaI S I-S 17.6 EGC = 2.4; PL = 30; GL = Karnataka, IndiaI S I-S 19.39 EGC = 2 (2 ˆ 1); PL = 30; GL = Karnataka, IndiaI S I-S 16.4 EGC = 9 (2 ˆ 4.5); PL = 30; GL = Karnataka, IndiaI S I-S 15.25 EGC = 16 (4 ˆ 4); PL = 30; GL = Karnataka, IndiaI S I-S 21.57 EGC = 2.4 (2 ˆ 1.2); PL = 30; GL = Madhya Pradesh, IndiaI S I-S 12.76 EGC = 16 (2 ˆ 8); PL = 30; GL = Maharashtra, IndiaI S I-S 11.34 EGC = 16; PL = 30; GL = Maharashtra, IndiaI S I-S 27.5 EGC = 1.3 (2 ˆ 0.65); PL = 30; GL = Tamilnadu, IndiaI S I-S 18.62 EGC = 2.5 (2 ˆ 0.125); PL = 30; GL = Tamilnadu, IndiaI S I-S 30.99 EGC = 0.7 (2 ˆ 0.35); PL = 30; GL = Tamilnadu, IndiaI S I-S 23.76 EGC = 2; PL = 30; GL = Tamilnadu, IndiaI S I-S 13.53 EGC = 9 (2 ˆ 4.5); PL = 30; GL = Maharashtra, IndiaI S I-S 26.06 EGC = 1.5; PL = 30; GL = Maharashtra, IndiaI S I-S 20.58 EGC = 1.5; PL = 30; GL = Karnataka, IndiaI S I-S 21.44 EGC = 3 (2 ˆ 1.5); PL = 30; GL = Andhra Pradesh, IndiaI S I-S 14.13 EGC = 8 (2 ˆ 4); PL = 30; GL = Karnataka, India

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Table 1. Cont.

Source

CategorizationGHG Emissions

(gCO2e/kWh)

Additional Features

FacilityType

Electric PowerGeneration Capacity

UniqueCategory Code EGC (MW); CF (%); PL (years); GL

Varun et al. [15]

D S D-S 24.57 EGC = 5 (2 ˆ 2.5); PL = 30; GL = Uttarakhand, IndiaD S D-S 21.43 EGC = 8 (2 ˆ 4); PL = 30; GL = Arunachal Pradesh, IndiaD S D-S 29.19 EGC = 2 (2 ˆ 1); PL = 30; GL = Sikkim, IndiaD S D-S 27.94 EGC = 3 (3 ˆ 1); PL = 30; GL = Uttarakhand, IndiaD S D-S 33.66 EGC = 1 (2 ˆ 0.5); PL = 30; GL = Sikkim, IndiaD S D-S 23.68 EGC = 5 (2 ˆ 2.5); PL = 30; GL = Sikkim, IndiaD S D-S 20.5 EGC = 9 (3 ˆ 3); PL = 30; GL = Sikkim, IndiaD S D-S 27.89 EGC = 2 (2 ˆ 1); PL = 30; GL = Arunachal Pradesh, IndiaD S D-S 21.12 EGC = 6 (3 ˆ 2); PL = 30; GL = Arunachal Pradesh, IndiaD S D-S 31.46 EGC = 0.9 (3 ˆ 0.3); PL = 30; GL = Jammu & Kashmir, IndiaD S D-S 18.87 EGC = 4 (2 ˆ 2); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 23.17 EGC = 2 (2 ˆ 1); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 48.23 EGC = 0.2 (2 ˆ 0.1); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 20.18 EGC = 4.5 (2 ˆ 2.25); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 37.52 EGC = 1 (2 ˆ 0.5); PL = 30; GL = Uttarakhand, IndiaD S D-S 29.12 EGC = 2 (2 ˆ 1); PL = 30; GL = Sikkim, IndiaD S D-S 25.05 EGC = 4.5 (2 ˆ 2.25); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 31.2 EGC = 1 (2 ˆ 0.5); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 32.57 EGC = 0.9 (2 ˆ 0.45); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 34.03 EGC = 0.8; PL = 30; GL = Himachal Pradesh, IndiaD S D-S 29 EGC = 3 (2 ˆ 1.5); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 24.22 EGC = 3 (2 ˆ 1.5); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 22.99 EGC = 3 (2 ˆ 1.5); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 23.99 EGC = 5 (2 ˆ 2.5); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 21.12 EGC = 3 (2 ˆ 1.5); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 26.7 EGC = 1.8 (2 ˆ 0.9); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 27.12 EGC = 1 (2 ˆ 0.5); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 30.58 EGC = 1 (2 ˆ 0.5); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 28.71 EGC = 1 (2 ˆ 0.5); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 22.66 EGC = 3 (2 ˆ 1.5); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 14 EGC = 21; PL = 30; GL = Kerala, IndiaD S D-S 25.11 EGC = 2 (2 ˆ 1); PL = 30; GL = Uttar Pradesh, IndiaD S D-S 21.03 EGC = 3 (3 ˆ 1); PL = 30; GL = Uttar Pradesh, IndiaD S D-S 20.58 EGC = 3 (3 ˆ 1); PL = 30; GL = Uttarakhand, IndiaD S D-S 22.85 EGC = 3 (3 ˆ 1); PL = 30; GL = Uttarakhand, IndiaD S D-S 28.12 EGC = 1 (2 ˆ 0.5); PL = 30; GL = Uttarakhand, IndiaD S D-S 22.01 EGC = 3 (3 ˆ 1); PL = 30; GL = Uttarakhand, IndiaD S D-S 27.16 EGC = 3 (2 ˆ 1.5); PL = 30; GL = Uttarakhand, India

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Table 1. Cont.

Source

CategorizationGHG Emissions

(gCO2e/kWh)

Additional Features

FacilityType

Electric PowerGeneration Capacity

UniqueCategory Code EGC (MW); CF (%); PL (years); GL

Varun et al. [15]

D S D-S 26.63 EGC = 6 (2 ˆ 3); PL = 30; GL = Uttarakhand, IndiaD S D-S 49.18 EGC = 0.3 (3 ˆ 0.1); PL = 30; GL = Jammu & Kashmir, IndiaD S D-S 43.36 EGC = 0.6 (3 ˆ 0.2); PL = 30; GL = Himachal Pradesh, IndiaD S D-S 29.18 EGC = 6 (2 ˆ 3); PL = 30; GL = Arunachal Pradesh, IndiaD S D-S 43.06 EGC = 0.75 (3 ˆ 0.25); PL = 30; GL = Arunachal Pradesh, IndiaD S D-S 41.91 EGC = 0.75 (3 ˆ 0.25); PL = 30; GL = Arunachal Pradesh, IndiaD µ D-µ 74.87 EGC = 0.05 (2 ˆ 0.025); PL = 30; GL = Uttarakhand, IndiaD S D-S 55.87 EGC = 0.1 (2 ˆ 0.05); PL = 30; GL = Uttarakhand, IndiaD S D-S 25.85 EGC = 6 (2 ˆ 3); PL = 30; GL = Arunachal Pradesh, IndiaD µ D-µ 59.65 EGC = 0.05 (2 ˆ 0.025); PL = 30; GL = Uttarakhand, IndiaD S D-S 62.86 EGC = 0.1 (2 ˆ 0.05); PL = 30; GL = Uttarakhand, IndiaD S D-S 49.24 EGC = 0.2 (2 ˆ 0.1); PL = 30; GL = Uttarakhand, IndiaD S D-S 21.98 EGC = 4; PL = 30; GL = Maharashtra, IndiaD S D-S 15.96 EGC = 25 (2 ˆ 12.5); PL = 30; GL = Orissa, IndiaD S D-S 18.26 EGC = 12 (3 ˆ 4); PL = 30; GL = Orissa, IndiaD S D-S 27.24 EGC = 3 (2 ˆ 1.5); PL = 30; GL = Uttarakhand, IndiaD S D-S 26.95 EGC = 3 (2 ˆ 1.5); PL = 30; GL = Uttarakhand, IndiaD S D-S 22.76 EGC = 3 (2 ˆ 1.5); PL = 30; GL = Uttarakhand, IndiaD S D-S 32.49 EGC = 3 (2 ˆ 1.5); PL = 30; GL = Arunachal Pradesh, IndiaD S D-S 74.79 EGC = 2 (2 ˆ 1); PL = 30; GL = Arunachal Pradesh, IndiaD S D-S 31.74 EGC = 3 (3 ˆ 1); PL = 30; GL = Uttar Pradesh, IndiaD S D-S 35.49 EGC = 3 (3 ˆ 1); PL = 30; GL = Uttarakhand, India

Arnøy and Modahl [16] D L D-L 2.19 EGC = 52.5; PL = 100; GL = Embretsfoss, Norway

Arnøy and Modahl [17] I L I-L 0.61 EGC = 130; PL = 100; GL = Trollheim, Norway

Donnelly et al. [18] I L I-L 15 EGC = 1000; CF = 57.5; PL = 100D L D-L 5 EGC = 100; CF = 57.5; PL = 100

Environmental Product Declaration Report [19] D S D-S 5.23 EGC = 2.1; PL = 100; GL = Zürich, Switzerland

Gallagher et al. [20]D S D-S 5.46 EGC = 0.65; PL = 50; GL = North Wales, UKD S D-S 7.39 EGC = 0.1; PL = 50; GL = North Wales, UKD µ D-µ 8.93 EGC = 0.05; PL = 50; GL = North England, UK

Gallagher et al. [21]MHPW µ MHPW-µ 2.14 EGC = 0.015; PL = 30; GL = UKMHPW µ MHPW-µ 4.36 EGC = 0.09; PL = 30; GL = IrelandMHPW S MHPW-S 2.78 EGC = 0.14; PL = 30; GL = UK

Hanafi and Riman [22] D S D-S 1.2 EGC = 9; PL = 50; GL = Simalungun, Indonesia

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3.2. Statistical Evaluation of Hydro LCA Studies

Figure 1 provides a graphical representation of the (a) error bars (mean ˘ 95% confidence interval(CI) statistics) and (b) box plots (quartiles + outlier statistics) for GHG emissions from the differenthydroelectricity generation systems reviewed in this study. Table 2 provides a statistical summaryof the life cycle GHG emissions with details on the sample size (N), mean (X) ˘ standard deviation(SD), minimum (Min.), maximum (Max.), standard error of the mean (SE), quartile 1 (Q1), quartile 2or median (Q2), and quartile 3 (Q3) for the different hydroelectricity generation systems reviewed inthis study.

From Figure 1a and Table 2, one may note that the mean life cycle GHG emissions obtained fromthe use of I-S, I-L, D-µ, D-S, D-L, PS-L, MHPW-µ, and MHPW-S hydroelectricity generation systemsare 21.05 gCO2e/kWh, 40.63 gCO2e/kWh, 47.82 gCO2e/kWh, 27.18 gCO2e/kWh, 3.45 gCO2e/kWh,256.63 gCO2e/kWh, 19.73 gCO2e/kWh, and 2.78 gCO2e/kWh, respectively. In the case ofimpoundment hydroelectricity generation systems, the mean life cycle GHGs emitted from largehydroelectricity generation systems (I-L) was more than the mean life cycle GHGs emitted fromsmall hydroelectricity generation systems (I-S). The higher mean life cycle GHG emissions fromlarge electricity generation capacity impoundment systems may be attributed to the activities ofconstruction (mining, steel, concrete) and the flooding of vegetated land [15,23]. Additionally,one may also note that the use of an alternative back-up power generation system (e.g., thermalpower generation system) to account for the seasonal variations in hydroelectricity generation supplycan result in a significant increase of the life cycle GHG emissions from the I-L hydroelectricitygeneration systems [4,23]. Two studies [15,28] noted the life cycle GHG emissions from impoundmenthydroelectricity generation systems to be directly proportional to the gross static head (distancebetween the intake and the turbine).

In the case of diversion hydroelectricity generation systems, the mean life cycle GHG emissionsfrom micro hydroelectricity generation systems (D-µ) was more than the mean life cycle GHG emissionsfrom small hydroelectricity generation systems (D-S) and large hydroelectricity generation systems(D-L). The mean life cycle GHG emissions decreased with an increase in the electricity generationcapacity for diversion hydroelectricity generation systems. From Figure 1a and Table 2, one maynote that the mean life cycle GHG emissions were minimum for the D-L hydroelectricity generationsystems (considering the hydroelectricity generation system categories with a representation of at leasttwo cases). The diversion hydroelectricity generation systems emitted less GHGs in comparison tothe impoundment hydroelectricity generation systems across the large electricity generation capacitycategory (refer to Figure 1a and Table 2). Similar observations were made by another study that notedthe run-off hydroelectricity generation systems to emit lower GHG emissions than the impoundmenthydroelectricity generation systems [23].

The mean life cycle GHG emissions were found to be the highest for PS-L hydroelectricitygeneration systems. The higher mean life cycle GHG emissions for PS-L hydroelectricity generationsystems may be attributed to the higher cumulative energy demand (approximately three times thecumulative energy demand required for diversion and impoundment hydroelectricity generationsystems) for consumption by the pumps [13].

The mean life cycle GHG emissions from miscellaneous hydropower works was less than themean life cycle GHG emissions from diversion hydroelectricity generation systems across the microelectricity generation capacity category (refer to Figure 1a and Table 2). The lower GHG emissionsfrom miscellaneous hydropower works may be attributed to the requirement of less constructionactivities than in the case of diversion hydroelectricity generation systems. The use of existingwater infrastructures to generate electricity at micro levels for local consumption was noted to be anenvironmental-friendly option that needs more investigation in the future. More LCA studies utilizingMHPW-S hydroelectricity generation systems are to be considered before one generalizes the influenceof MHPW-S on the mean life cycle GHG emissions.

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Figure 1. GHG emissions from hydroelectricity generation systems: (a) mean ± 95% CI error bars and (b) quartile box plots. 

Figure 1. GHG emissions from hydroelectricity generation systems: (a) mean ˘ 95% CI error bars and (b) quartile box plots.

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Table 2. GHG emission (gCO2e/kWh) statistics from hydroelectricity generation systems.

Hydro System Type N X ˘ SD Min. Max. SE Q1 Q2 Q3

I-S 24 21.05 ˘ 6.25 11.34 33.86 1.28 15.25 21.01 25.6I-L 8 40.63 ˘ 80.57 0.61 237 28.49 1.56 10.43 16.64D-µ 3 47.82 ˘ 34.53 8.93 74.87 19.93 8.93 59.65 74.87D-S 133 27.18 ˘ 10.38 1.2 74.79 0.9 22.66 27.1 31.56D-L 3 3.45 ˘ 1.43 2.19 5 0.82 2.19 3.16 5PS-L 3 256.63 ˘ 314.35 5.6 609.2 181.49 5.6 155.1 155.1

MHPW-µ 3 19.73 ˘ 28.57 2.14 52.7 16.5 2.14 4.36 52.7MHPW-S 1 2.78 ˘ 0 2.78 2.78 0 2.78 2.78 2.78

From Figure 1b, one may note that the degree of variation in GHG emissions was minimal for D-Lhydroelectricity generation systems, followed by D-S, I-S, I-L, MHPW-µ, D-µ, and PS-L hydroelectricitygeneration systems. The degree of variation being less indicates the level of maturity and consistency inthe use advanced technology in the various stages of life cycle analysis, irrespective of the geographicallocations and many other influential factors. Note that the standard deviation values for I-L and PS-Lhydroelectricity generation systems are more than the corresponding mean values (refer to Table 2),thereby indicating that there is a large variation in the use of technology across different geographiclocations. In the context of both the mean life cycle GHG emissions and the degree of variation inGHG emissions from D-L hydroelectricity generation systems being minimal, this study identifies thediversion hydroelectricity generation systems with large electricity generation capacity to be the mostenvironmental-friendly option amongst the different categories of hydroelectricity generation systemsconsidered in this study.

4. Conclusions

This paper evaluated the life cycle GHG emissions from hydroelectricity generation systems bydeveloping a new categorization index that integrated the names of the two classification systemsbased on the facility type (I, D, PS, MHPW) and the electric power generation capacity (µ, S, L). A totalof 19 hydroelectricity generation system LCA studies that summarized 178 representative cases wereidentified in the literature and reviewed in this study. Each of the reviewed hydroelectricity generationsystem LCA studies was first assigned a unique category code in accordance with the developedcategorization index. The categorization of the reviewed 19 hydroelectricity generation system LCAstudies yielded a total of eight distinct categories, namely, I-S, I-L, D-µ, D-S, D-L, PS-L, MHPW-µ,and MHPW-S.

The mean life cycle GHG emissions from I-S, I-L, D-µ, D-S, D-L, PS-L, MHPW-µ, and MHPW-Shydroelectricity generation systems are 21.05 gCO2e/kWh, 40.63 gCO2e/kWh, 47.82 gCO2e/kWh,27.18 gCO2e/kWh, 3.45 gCO2e/kWh, 256.63 gCO2e/kWh, 19.73 gCO2e/kWh, and 2.78 gCO2e/kWh,respectively. The mean life cycle GHG emissions from I-L hydroelectricity generation systems werenoted to higher than the mean life cycle GHG emissions from I-S electric generation systems (therelatively higher GHG emissions for I-L hydroelectricity generation systems being attributed tothe dam construction activities, the flooding of vegetated land, and the use of back-up power).The mean life cycle GHGs emitted from D-L hydroelectricity generation systems was more thanthe mean life cycle GHGs emitted from D-S and D-µ hydroelectricity generation systems. Forthe case of large hydroelectricity generation systems, the mean life cycle GHG emissions fromdiversion hydroelectricity generation systems was less than the mean life cycle GHG emissionsfrom impoundment hydroelectricity generation systems. D-L hydroelectricity generation systemsprovided the most environmental-friendly option with the lowest mean life GHG emissions andminimal variations between the reviewed D-L LCA case representations (considering only thehydroelectricity generation system categories with a representation of at least two cases). PS-Lhydroelectricity generation systems had the highest mean life cycle GHG emissions due to the

Sustainability 2016, 8, 539 13 of 14

higher energy consumption by pumps. For micro electricity generation capacity, the miscellaneoushydropower works emitted less GHGs than the diversion hydroelectricity generation systems dueto limited emissions from construction activities. There was only one LCA case representation notedin the literature for MHPW-S systems. Future research needs to focus on the development of morehydro LCA studies (that includes comprehensive details on the site-specific characteristics of thehydroelectricity system) with emphasis on MHPW-S systems.

Acknowledgments: This work was supported by the US National Science Foundation through the CREST Centerfor Energy and Environmental Sustainability (CEES) at Prairie View A&M University, award number 1036593.

Author Contributions: Akhil Kadiyala conceived the approach to scrutinize hydroelectricity life cycle GHGemissions in-detail and developed the manuscript under the guidance of Professors Raghava Kommalapati andZiaul Huque.

Conflicts of Interest: The authors declare no conflict of interest.

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